Lorenzo, GuillermoDi Muzio, Nadia GisellaDeantoni, Chiara LucreziaCozzarini, CesareFodor, AndreiBriganti, AlbertoMontorsi, FrancescoPérez-García, Víctor M.Gómez, HéctorReali, Alessandro2024-10-142024-10-142022Lorenzo, G., di Muzio, N., Deantoni, C. L., Cozzarini, C., Fodor, A., Briganti, A., Montorsi, F., Pérez-García, V. M., Gomez, H., & Reali, A. (2022). Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse. iScience, 25(11). https://doi.org/10.1016/J.ISCI.2022.105430http://hdl.handle.net/2183/39604[Abstract:] The detection of prostate cancer recurrence after external beam radiotherapy relies on the measurement of a sustained rise of serum prostate-specific antigen (PSA). However, this biochemical relapse may take years to occur, thereby delaying the delivery of a secondary treatment to patients with recurring tumors. To address this issue, we propose to use patient-specific forecasts of PSA dynamics to predict biochemical relapse earlier. Our forecasts are based on a mechanistic model of prostate cancer response to external beam radiotherapy, which is fit to patient-specific PSA data collected during standard posttreatment monitoring. Our results show a remarkable performance of our model in recapitulating the observed changes in PSA and yielding short-term predictions over approximately 1 year (cohort median root mean squared error of 0.10–0.47 ng/mL and 0.13 to 1.39 ng/mL, respectively). Additionally, we identify 3 model-based biomarkers that enable accurate identification of biochemical relapse (area under the receiver operating characteristic curve > 0.80) significantly earlier than standard practice (p < 0.01).engAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/OncologyBiological sciencesSystems biologyCancerjournal articleopen access10.1016/j.isci.2022.105430